EM algorithm for stochastic hybrid systems

03/19/2020
by   Masaaki Fukasawa, et al.
0

A stochastic hybrid system, also known as a switching diffusion, is a continuous-time Markov process with state space consisting of discrete and continuous parts. We consider parametric estimations of the Q matrix for the discrete state transitions and of the drift coefficient for the diffusion part based on a partial observation where the continuous state is monitored continuously in time, while the discrete state is unobserved. Extending results for hidden Markov models developed by Elliot et al. [1], we derive a finite-dimensional filter and the EM algorithm for stochastic hybrid systems.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/31/2021

The Expectation-Maximization Algorithm for Continuous-time Hidden Markov Models

We propose a unified framework that extends the inference methods for cl...
research
05/30/2022

A Continuous Time Framework for Discrete Denoising Models

We provide the first complete continuous time framework for denoising di...
research
01/31/2019

Geometric fluid approximation for general continuous-time Markov chains

Fluid approximations have seen great success in approximating the macro-...
research
01/13/2020

Decisiveness of Stochastic Systems and its Application to Hybrid Models

In [ABM07], Abdulla et al. introduced the concept of decisiveness, an in...
research
09/28/2020

Decisiveness of Stochastic Systems and its Application to Hybrid Models (Full Version)

In [ABM07], Abdulla et al. introduced the concept of decisiveness, an in...
research
03/03/2018

Stochastic Resonance for a Model with Two Pathways

In this thesis we consider stochastic resonance for a diffusion with dri...
research
12/07/2021

Explicit approximations for nonlinear switching diffusion systems in finite and infinite horizons

Focusing on hybrid diffusion dynamics involving continuous dynamics as w...

Please sign up or login with your details

Forgot password? Click here to reset